(Senior) Data Scientist - Personalisation (m/f/n)

InPost; Kraków; On-site; PLN 133,920 - 200,880; Full time

Benefits offered by this job

Innovative work environment

Professional development opportunities

Collaboration with cross-functional teams

Job summary

A leading technology firm in Poland is seeking an experienced Data Scientist to join its Data & AI team. You will leverage advanced analytical techniques and machine learning models to drive strategic decisions and optimize marketing strategies. The ideal candidate has at least 3 years of experience in data science, proficiency in Python, and strong communication skills. This role offers innovative challenges and opportunities for professional development in a collaborative environment.

Qualifications

• At least 3 years of commercial experience as a Data Scientist.
• Proficient in Polish and English; knowledge of other languages is a plus.
• Skilled in understanding business needs and communicating insights.

Responsibilities

• Partner with Product and Business Teams to provide actionable insights.
• Develop and implement data science solutions to optimize marketing strategies.
• Collaborate with cross-functional teams to ensure data-driven initiatives.
• Stay updated with cutting-edge methods and trends in Data Science & AI.
• Communicate insights and recommendations to the management.

Skills

Goal-oriented

Independent

Change management skills

Time management

Communication skills

Problem-solving

Education

Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Econometrics

Tools

Python 3

ML libraries (Pandas, Numpy, Scipy, Scikit-learn)

PySpark

Cloud solutions (Databricks, Azure, GCP, AWS, Snowflake)

Job description

• Full-time
• Direction: Data & AI - InPost Group
• Organisation: InPost Group

Company Description

InPosthas revolutionised e-commerce parcel delivery in Poland and is now one of Europe’s leading OOH e-commerce enablement platforms. Founded in 1999 by Rafał Brzoska, InPost provides delivery services through our network of almost 47,000 Automated Parcel Machines (APMs) and almost 35,000 pick-up drop-off points (PUDO) in nine countries across Europe, as well as to-door courier and fulfilment services to e-commerce merchants. InPost’s lockers provide consumers with a cheaper and more flexible, convenient, environmentally friendly and contactless delivery option.

We areseekingtalented and passionate Data Scientists to join our Personalization Hub. In this role, you willleverageadvanced analytical techniques and machine learning models to extract actionable insights from our complex data sets, driving strategic decision-making and operational excellence. You will collaborate closely with cross-functional teams to develop innovative solutions that enhance ourlogisticsoperations, improve efficiency, and elevate the customer experience.

If youhave specialized knowledgein user,productand/or marketing data science (or want topossessit) - we would very much like to meet you! :)

Job Description

On a daily basisyou will:

• Partner with our Product and Business Teamsto understand their needs, translate them into data science solutions, andprovideactionable insights.We work with all business products withinInPost, e.g.InPostMobile, Loyalty Programme,InPostPay, among others.
• Develop and implement data science solutions(ML models,GenAIproducts,hybrid approaches, data analytics)tooptimizemarketing and products strategies, enhance user experience and shape targeting.
• Collaborateclosely with cross-functional teams(e.g. otherData&AIteams, Technology teams)to ensure seamless integration of data-driven initiatives.
• Stay ahead of the curveexploringcutting-edgemethods and being on top ofnew trendsin Data Science & AI.
• Communicateinsights and recommendations to the management and business teams, and other data community members.
  

In summary – you will have an opportunity to conduct end-to-end data products:exploring business needs(skills: understanding business, communication),analyzeproblemsandpropose thesis (data analytics), develop a solution (skills: hands-onML/AI), presentinsights and results (skills:communication, translating technical stuff to non-technical people, ppt/BI), maintain the solution (skills: basic BI skills, model monitoring).

Qualifications

Job requirements:

• Education–Bachelor’s or Master’sdegree in a relevant field, e.g. Data Science, Computer Science, Mathematics, Econometrics
• Experience–you haveat least 3 years ofcommercialexperience as a Data Scientist. Consultingand marketing analyticsexperiencearea plus
• Mindset–you aregoal-orientedand independent,skilled inchange and time management, business-conscious,able to thinklong-termand decompose business problems
• Languages–you areproficientinPolish andEnglish(other languages knowledge is a plus).

Technical skills:

• Excellent knowledge of ML solutions and their impact on businessanduser experience (clustering, recommender systems, regression, classification, etc.).
• Hands-on experience with working withlarge amountsof data.
• ProficiencyinPython 3,as well asML and data analysis libraries(e.g. Pandas,Numpy,Scipy, Scikit-learn,Statsmodels, TF/Pytorch, etc.).
• Experience in writing well-structured code: functions, classes, modules.
• Knowledge and experience inPySpark, relational databases, cloud solutions(e.g. Databricks, Azure, GCP, AWS, Snowflake).

Nice to have:

• Experience inleveragingCI/CD pipelines in data-based products.
• Experiencewithdatapipelinesframework, preferablyKedro.
• Experience withCLI tools:bash/zsh.

Additional Information

• Impact:Your work will directly influence strategic decisions and operational efficiencies across multiple international markets.
• Innovation:Be part of the team that's pushing boundaries of data analytics, working with the latest technologies and methodologies.
• Growth:This role offers unparalleled opportunities for professional development in a data-driven, technology-forward environment.
• Collaboration:Engage with cross-functional teams, share knowledge and best practices, fostering a culture of continuous learning and improvement.